Volume 1 Number 3 (Sep. 2012)
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IJCCE 2012 Vol.1(3): 207-209 ISSN: 2010-3743
DOI: 10.7763/IJCCE.2012.V1.54

Fast Pedestrian Detection Based on Haar Pre-Detection

Wenfeng Xing, Yong Zhao, Ruzhong Cheng, Jiaoyao Xu, Shaoting Lv, and Xinan Wang

Abstract—We proposed a simple but efficient way to accelerate the traditional pedestrian process without decrease the detection accuracy. Haar/adaboost is one of the fastest ways in pattern recognition, and HOG/libSVM is an accurate way to deal with pedestrian detection. Haar/adaboost can work fast using low resolution images, but HOG/libSVM, which was proposed by Dalal in 2005, is much slower due to the high resolution detection window and complicated feature extraction. Inspired by the above results, we combine these two most popular ways to develop a better pedestrian detection system. And due to the fast small scale Haar/adaboost pre-detection, experiment result shows that the time our method consumed is about one third of the original HOG/LibSVM method, while maintaining almost the same detection rate.

Index Terms—Small scale, HOG, HAAR, fast pedestrian detection

The authors are with School of Computer and Information Engineering, Peking University Shen Zhen Graduate School, China (e-mail: springs@126.com)

Cite: Wenfeng Xing, Yong Zhao, Ruzhong Cheng, Jiaoyao Xu, Shaoting Lv, and Xinan Wang, "Fast Pedestrian Detection Based on Haar Pre-Detection," International Journal of Computer and Communication Engineering vol. 1, no. 3, pp. 207-209 , 2012.

General Information

ISSN: 2010-3743
Frequency: Quarterly
Editor-in-Chief: Dr. Maode Ma
Abstracting/ Indexing: EI (INSPEC, IET), Google Scholar, Crossref, Engineering & Technology Digital Library, ProQuest, and Electronic Journals Library
E-mail: ijcce@iap.org
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